{"id":"W3201545246","doi":"10.1093/ijl/ecab007","title":"Names of Feelings in the Dictionary","year":2021,"lang":"en","type":"article","venue":"International Journal of Lexicography","topic":"Language, Metaphor, and Cognition","field":"Psychology","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Lexicographical order; Psyche; Feeling; Linguistics; Schema (genetic algorithms); Lexical item; Psychology; Component (thermodynamics); Anger; Computer science; Natural language processing; Artificial intelligence; Social psychology; Mathematics; Philosophy; Information retrieval; Combinatorics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005996979,0.0004565037,0.000416643,0.002498377,0.00192789,0.003805136,0.0004516805,0.0005494779,0.01617047],"category_scores_gemma":[0.002264332,0.0002213208,0.0002476726,0.003622735,0.003565678,0.005501374,0.00176736,0.001345609,0.002055547],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001378352,"about_ca_system_score_gemma":0.001022409,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001725238,"about_ca_topic_score_gemma":0.001927338,"domain_scores_codex":[0.9988962,0.0005172845,0.0001690134,0.0001529128,0.0001713743,0.00009325219],"domain_scores_gemma":[0.9988657,0.0005263935,0.0000872059,0.0001415262,0.0002901963,0.00008907627],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001657034,0.00002173942,0.00139324,0.0003970911,0.000009945078,0.0002361702,0.01158999,0.0001053712,0.002734584,0.9074512,0.02308875,0.0528063],"study_design_scores_gemma":[0.00004065837,0.00007306839,0.004459193,0.0006227414,0.00002240756,0.001386698,0.01275561,0.001104744,0.002146006,0.1503569,0.8269745,0.00005746295],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1781974,0.009242692,0.09897556,0.008186928,0.00343342,0.000366983,0.007199806,0.001152559,0.6932447],"genre_scores_gemma":[0.9265957,0.002480068,0.03273889,0.001097075,0.0004109014,0.0002427422,0.004252001,0.0006371457,0.0315455],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01617047,"threshold_uncertainty_score":0.05409563,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01823372860466204,"score_gpt":0.320349516575356,"score_spread":0.302115787970694,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}